I first heard the reference, "standing on the shoulders of giants," from a colleague at RAND, (one of the three "Daves" who taught me so much), whose gentle humility and formidable intellect led me to believe he had created the phrase. Later, I came to realize this is a common phrase used to describe the core business model for academe and science - we learn from the inquiry that went before us in order to reach higher. I ruin the phrase here with some trepidation. However, it communicates well my personal angst as I observe thought experiments which appear to lack an awareness of the science that has gone before.

First though, a story.

A former colleague and friend, (not a Dave) whose company I miss greatly, was saved from certain death by the recognition-primed decision ability of his emergency room physician. Stranded for three days on a mountainside following a blizzard, my friend had severe frostbite affecting his hands, feet and face. The physician, before any other decision, immediately began treating my friend with antibiotics, even though there were no overt signs of infection. The good doctor had experience with a fast-moving and deadly opportunistic infection syndrome that targets frostbite victims. Because of the severity of his wounds, my friend was down to hours of life had this infection not been treated.

The physician acted on metaphor, saving a life. My friend lost part of his nose, all his toes, and the sense of touch in several fingers (I hope he forgives the title of this post, and accompanying photo, now that I think of it). He endured nine root canals in one day, and months of rehabilitation. However, he is alive, and gets about without prosthetics, thanks to the physician's reliance on recognition-primed decision making.

Regarding my reference above, Gary Klein defines the Recognition-Primed Decision model thus: "[it] fuses two processes: the way decision makers size up the situation to decide which course of action makes sense, and the way they evaluate to evaluation that course of action by imagining it." (p.24)

Klein, in a his ground-breaking work regarding decision-making, shares the findings from a decade doing field research: decisions are not made according to classic methods of rational choice theory, but closer to Simon's satisficing model. Rather than using deductive logical thinking, analysis of probabilities, and statistical methods; we actually employ intuition, mental stimulation, metaphor and storytelling.

Intuition: size up a situation quickly
Mental stimulation: imagine how a course of action might be carried out
Metaphor: draw on our experience by suggesting parallels between the current situation and something else we have come across.
Storytelling: consolidate our experiences to make them available in the future, either to ourselves or to others.

Why is all this relevant to me today?

My recent reference to the death of Knowledge Management (KM) in the Defense Department appears to have sparked some reaction - most of it aimed at this silly pundit who fails to realize either the successful KM at the grassroots level, or the need for consolidation of intent at the highest levels in order to ensure the success of KM throughout the Department.

One interesting email chain consisting of 63+ voices (most of them silent, I'm not that provocative after all) supplies most of my information regarding the negative response. (I have received welcome words of encouragement as well, omitted here for brevity.) For the most part, folks feel I unfairly declared KM dead in a most unhelpful manner and at a most inopportune moment - and am utterly mistaken. The fact that so many professionals are working in the field, trying to advance the principles of KM in the Department, surely proves me wrong. In addition, how can an effort to gain status, standing, and funding for KM efforts at a higher level be attacked as misguided? Should not we applaud such efforts, rather than snipe from the sideline? If I only understood how things work in DoD, I would realize that without some visibility and senior leader buy-in for KM programs, the whole exercise would never gain traction in an enduring fashion.

Given a precept for KM, i.e., the overall value is to enable better decision-making and actions, I submit we should gauge the likely relevance and utility of KM efforts against the ability to effect better decisions - in the context of what we know from research into naturalistic decision-making inquiry.

Some excellent points are made by Bill Kaplan in comments to my original post, and by some justifiably emotional voices on the email chain I referenced earlier: Grassroots efforts do exist and thrive, but they have failed to scale across the Department or to effect the lasting change for which we all hope. Intellipedia has the promise to transform our notion regarding finished intelligence - but a thoughtful professional in the IC went out of her way to inform me that even this effort still faces effective organizational antibodies.

(As an aside, this conversation with the IC professional occurred in an atmosphere of deeply shared context and using a high degree of trust built over past conversations - with a woman I have never met or spoken with outside the Twitter communications "channel." Perhaps one idea for DoD KM lies in advising Information Security professionals to open up closed social media channels?)

My other examples (AFKN, etc.) likewise have not transformed the Department, but have enjoyed limited diffusion, failing to achieve the elusive "network effect" that might lead to transformation.

Without some high air cover, even Intellipedia, this jewel of federal social media and distributed cognition, could face marginalization or cancellation. Were it not for some managers who "get it," grassroots efforts appear doomed to provide lasting success. How could I argue against the very efforts that are trying to scale and sustain the grassroots? My quick answer: because they will fail, for lack of learning from what works. Bill Kaplan, again, provides context from a practitioner view - read his comment to learn more. In addition to this practitioner view, the science (Klein, others) is clear regarding the naturalistic decision making processes that should be targeted if we are to improve decisions.

Therefore: what KM methods best prepare us for better decisions? What is the role of portals and repositories if we rely on the experiential knowledge that fuels intuition? Of what use is a workforce "trained" in KM if we learn by experience and through the collection of fragmented narrative? What on Earth do "common KM metrics" mean to situational context that is extremely local?

The central question, perhaps, is one of innovation. KM professionals have grasped a view of methods and principles that must fuel innovation in the ways we decide, act, and operate. The trick now is to scale iterative innovation (grassroots initiatives) and enable disruptive innovation (changes to business models resulting from these grassroot "beautiful exceptions"). (Apologies to my new colleagues, who taught me this excellent phrase in the context of educational innovation.)

KM may be dead, or not, in DoD, but debating that is not all that useful. Instead, why not consider how to scale successes and transform operations; based on what the very much alive KM professionals have accomplished so far in DoD and across the federal and private sectors. And in doing so, why not learn from examples where innovative ideas and methods have transformed industries and social endeavors? Two examples of private sector innovation include:

Lockheed Martin's "skunkworks," a division that operated free of any corporate process or overhead in order to incubate a radically new business model.
Charles Schwab's embrace of online trading within a subsidiary that featured an entirely new sales staff with different compensation schedules - again to incubate a new business model. Clayton Christensen favorably compares this to Merrill Lynch (remember them?), who tried to incorporate, in a literal use of that term, online trading into their existing business model - to mixed results.

Where has innovation ever been realized through centralized training programs, common metrics and standards, or a maturity model? Let's return to first principles - consider the inquiry that has gone before, and consider also the knowledge needs of that young person on that mountain far away. Disclaimer: As with so many of you, and likely of those among the 63+, one of those young people is family to me. I dearly wish to see him succeed - and to embrace him again someday.